Space invariant vehicle recognition for toll plaza monitoring and auditing system

Abstract

Space invariant object recognition is one of the difficult problems of pattern recognition and has many potential applications. In this paper, a vehicle recognition system is proposed for toll plaza monitoring and auditing. This system recognizes the type of approaching vehicle such as truck, bus, car etc. irrespective of geometrical distortion of vehicles such as scale and rotation. Maximum Average Correlation Height (MACH) filter is used to obtain out-of-plane rotation invariance and Log rMapping is employed to achieve in-plane and scale invariance. Five classes of vehicles are defined: trucks, buses, wagons, cars and motorcycles. MACH filter is trained on log r-maps of each class of vehicles for range of orientation and correlated sequentially with the log r-map of region of interest. The type of vehicle is recognized from correlation results. The system analyzes the real time toll plaza video and generates audit report indicating the total count of each type of vehicles during a specified time and the resulted toll collection according to their respective charges. The system also generates monitoring alerts as per given decision rules.

Vehicle Number Plate Recognition System: A Literature Review and Implementation using Template Matching

“…They applied canny edge detection to detect the presence of vehicle and SVM to recognize the vehicle. In [12], Maximum Average Correlation Height (MACH) filter and Log r-theta Mapping techniques were applied to recognize the type of vehicle irrespective of scale and rotation variation of vehicles. The MACH filter was used for detection of targets in cluttered environment.…”

“…In the last stage, characters are segmented from the Number Plate so that only useful information is retained for recognition where the image format will be converted into characters [1].Various research journals were consulted to find relevant information regarding ANPR based applications. ANPR systems are based on common approaches like Artificial Neural Network (ANN) [2,3],Probabilistic neural network (PNN) [4], Optical Character Recognition (OCR) [5,3], MATLAB [6], Configurable method [7], Sliding Concentrating window (SCW), Back-Propagation Neural Network [8], Support Vector Machine (SVM) [9], Inductive Learning [10], Regionbased, Color Segmentation [11] and Fuzzy-Based Algorithm [12], Scale Invariant Feature Transform (SIFT) [13].…”

Video Sensor-Based Automatic License Plate Recognition of Static and Moving Vehicles

“…They used canny edge detection to detect the presence of vehicle and SVM to recognize the vehicle plate. Maximum Average Correlation Height (MACH) filter and Log r-theta Mapping techniques were applied to recognize the type of vehicle irrespective of scale and rotation variation of vehicles [11]. The MACH filter was used for detection of targets in cluttered environment.…”

Development of Car Plate Number Recognition using Image Processing and Database System for Domestic Car Park Application

“…The Optical Character Recognition [2,3] is the first step for the recognition process. The next steps followed by the filtration in MATLAB toolbox [4], Color Segmentation [5] and Fuzzy-Based Algorithm [6].…”